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BioMed Research International
Volume 2016, Article ID 6186281, 14 pages
Review Article

Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks

1Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
2Cancer Biology Program, Stanford University School of Medicine, Stanford, CA 94305, USA
3Division of Biomedical Informatics, University of California, San Diego, La Jolla, CA 92093, USA
4Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
5Department of Genetics, Harvard Medical School, Boston, MA 02115, USA

Received 1 January 2016; Revised 23 April 2016; Accepted 8 May 2016

Academic Editor: Eugenio Ferreira

Copyright © 2016 Shengda Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative “OMICs” arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA), the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT) and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine.